аЯрЁБс>ўџ 68ўџџџ5џџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџџьЅС9 јП!bjbj§Я§Я 5"ŸЅŸЅ!џџџџџџl*******>pppp„>xдЄКККККККЦ Ш Ш Ш Q p‰ pљ$L lp*КККККф**КК2фффК*К*КЦ фКЦ фжфК **К К˜ @эсЋ9Т>2pТК К H0xК мТ"мК ф>>****йCALL FOR PAPERS BIOKDD-CBGI'03 Biological Knowledge Discovery and Data Mining Session of Atlantic Symposium on Computational Biology and Genome Information Systems & Technology (CBGI'03) Cary, North Carolina, U.S.A. September 26-30, 2003 With the development of Molecular Biology during the last decades, we are witnessing an exponential growth of both the volume and the complexity of biological data. The Human Genome Project is providing the sequence of the 3 billion DNA bases that constitute the human genome. And, consequently, we are provided too with the sequences of about 100,000 proteins. Therefore, we are entering the post-genomic era : After having focused so much efforts on the accumulation of data, we have now to focus as much efforts, and even more, on the analysis of these data. This will enable us to learn more about gene expression, protein interactions and other biological mechanisms. Analyzing this huge volume of data is a challenging task because, not only, of its complexity and its multiple numerous correlated factors, but also, because of the continuous evolution of our understanding of the biological mechanisms. Classical approaches of biological data analysis are no longer efficient and produce only a very limited amount of information, compared to the numerous and complex biological mechanisms under study. Actually, these approaches use only a very limited number of parameters, to represent the so-many correlated factors involved in the biological mechanisms. From here comes the necessity to use computer tools and develop new in silico high performance approaches, to support us in the analysis of biological data. And, hence, to help us in our understanding of the correlations that exist between, on one hand, structures and functional patterns of biological sequences, i.e., DNA, RNA and proteins, and, on the other hand, genetic and biochemical mechanisms. Knowledge Discovery and Data mining (KDD) are a response to these new trends : Knowledge discovery is an emerging field where we combine techniques from Algorithmics, Artificial Intelligence, Mathematics and Statistics to deal with the theoretical and practical issues of extracting knowledge, i.e., new concepts or concept relationships, hidden in volumes of raw data. Knowledge discovery offers the capacity to automate complex search and data analysis tasks. We distinguish two types of knowledge discovery systems : verification systems and discovery ones. Verification systems are limited to verifying the users hypothesis, while, discovery ones autonomously predict and explain new knowledge. Biological knowledge discovery process should provide for the selection of the appropriate data mining approaches by taking into account both the characteristics of the biological data and the general requirements of knowledge discovery process. Data mining is one of the pre-processing steps in the knowledge discovery process. It consists in extracting nuggets of information, i.e., pertinent patterns, pattern correlations, estimations or rules, hidden in bodies of data. The extracted information will be used in the verification of hypothesis or the prediction and explanation of knowledge. Biological data mining aims at extracting motifs, functional sites or clustering/classification rules from biological sequences. Numerous techniques suitable for data mining in Molecular Biology are available, however, the selection of ad hoc ones is non-trivial. In our session, we are interested in papers that deal with issues of biological KDD. INSTRUCTIONS TO AUTHORS You are invited to submit a hardcopy or a pdf version of a draft paper, about 4 to 5 pages including figures and references, before May 1, 2003 to the Session Chair: Dr. Mourad Elloumi, Mailing Address: Cite Intilak bloc 6, app. 7, El Menzah 6, 2091 Tunis, Tunisia. Phone: +216 71 233 253 Fax : +216 71 712 093 E.Mail:  HYPERLINK "mailto:Mourad.Elloumi@fsegt.rnu.tn" Mourad.Elloumi@fsegt.rnu.tn BIG: www.groups.yahoo.com/group/bioinformaticsgroup URL: www.MouradElloumi.homestead.com/home.html IMPORTANT DATES May 1, 2003 : Draft papers (about 4 to 5 pages) due June 1, 2003 : Notification of acceptance July 1, 2003 : Camera-Ready papers & Prereg. due September 26 - 30, 2003: CBGI'03 Conference !R]ѓєБ* 3 y œ Щ м • ž ‚ – › Љ +6˜ŸщЈМ]–œžŸЯабьэюѓ!"'QRbѕыѕтѕмзбзбзбзбзбзбзбзбзбзмззЬзХХЖХЄЖ›ЖХ”‡|”|змCJOJQJmH sH CJOJQJ^JmH sH  CJmH sH 0JCJOJQJ#jCJOJQJUmH sH jCJOJQJUmH sH  CJOJQJmHsH 6mH sH mH sH  5mH sH CJaJmH sH 5CJ(aJ(mH sH 5CJaJmH sH 0!"#R]ПмђѓєЩ +’шщЇњњњњњњѓѓфззЮЮСССИИЖ­$„0`„0a$$„`„a$ $„:„]„:`„a$$„.^„.a$ $„`„R]„`^„Ra$$„п„ŠЄ№]„п^„Ša$$Є№a$$a$!ўЇЈМъ?f}–ю"QRb—Тє!іььььььььььъъфффф„,`„, „№„7]„№`„7$„0`„0a$bѕ!ћmH sH 3 0hPАh. 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